RunyaoChen opened a new pull request, #39711:
URL: https://github.com/apache/spark/pull/39711
<!--
Thanks for sending a pull request! Here are some tips for you:
1. If this is your first time, please read our contributor guidelines:
https://spark.apache.org/contributing.html
2. Ensure you have added or run the appropriate tests for your PR:
https://spark.apache.org/developer-tools.html
3. If the PR is unfinished, add '[WIP]' in your PR title, e.g.,
'[WIP][SPARK-XXXX] Your PR title ...'.
4. Be sure to keep the PR description updated to reflect all changes.
5. Please write your PR title to summarize what this PR proposes.
6. If possible, provide a concise example to reproduce the issue for a
faster review.
7. If you want to add a new configuration, please read the guideline first
for naming configurations in
'core/src/main/scala/org/apache/spark/internal/config/ConfigEntry.scala'.
8. If you want to add or modify an error type or message, please read the
guideline first in
'core/src/main/resources/error/README.md'.
-->
### What changes were proposed in this pull request?
This PR improves error messages for `ARRAY` / `MAP` / `STRUCT` types without
element type specification. A new error class `INCOMPLETE_TYPE_DEFINITION` with
subclasses (`ARRAY`, `MAP`, and `STRUCT`) is introduced.
**Details**
In the case where we do `CAST AS` or `CREATE` a complex type without
specifying its element type,
e.g.
```
CREATE TABLE t (col ARRAY)
```
`[UNSUPPORTED_DATATYPE] Unsupported data type "ARRAY"` error would be
thrown, while we do support the `ARRAY` type and just require it to be typed.
This PR proposes a better error message like
```
The definition of `ARRAY` type is incomplete. You must provide an element
type. For example: `ARRAY\<INT\>`.
```
<!--
Please clarify what changes you are proposing. The purpose of this section
is to outline the changes and how this PR fixes the issue.
If possible, please consider writing useful notes for better and faster
reviews in your PR. See the examples below.
1. If you refactor some codes with changing classes, showing the class
hierarchy will help reviewers.
2. If you fix some SQL features, you can provide some references of other
DBMSes.
3. If there is design documentation, please add the link.
4. If there is a discussion in the mailing list, please add the link.
-->
### Why are the changes needed?
The previous error message for incomplete complex types is confusing. A
`UNSUPPORTED_DATATYPE` error would be thrown, while we do support complex
types. We just require complex types to have their element types specified. We
need a clear error message with an example in this case.
<!--
Please clarify why the changes are needed. For instance,
1. If you propose a new API, clarify the use case for a new API.
2. If you fix a bug, you can clarify why it is a bug.
-->
### Does this PR introduce _any_ user-facing change?
Yes, this PR changes the error message which is user-facing.
Error message before this PR:
```
spark-sql> SELECT CAST(array(1, 2, 3) AS ARRAY);
[UNSUPPORTED_DATATYPE] Unsupported data type "ARRAY"(line 1, pos 30)
```
Error message after this PR:
```
[INCOMPLETE_TYPE_DEFINITION.ARRAY] Incomplete complex type: The definition
of `ARRAY` type is incomplete. You must provide an element type. For example:
`ARRAY\<INT\>`.
```
Similarly for MAP and STRUCT types.
<!--
Note that it means *any* user-facing change including all aspects such as
the documentation fix.
If yes, please clarify the previous behavior and the change this PR proposes
- provide the console output, description and/or an example to show the
behavior difference if possible.
If possible, please also clarify if this is a user-facing change compared to
the released Spark versions or within the unreleased branches such as master.
If no, write 'No'.
-->
### How was this patch tested?
Added unit tests covering CAST and CREATE with ARRAY / STRUCT / MAP types
and their nested combinations.
<!--
If tests were added, say they were added here. Please make sure to add some
test cases that check the changes thoroughly including negative and positive
cases if possible.
If it was tested in a way different from regular unit tests, please clarify
how you tested step by step, ideally copy and paste-able, so that other
reviewers can test and check, and descendants can verify in the future.
If tests were not added, please describe why they were not added and/or why
it was difficult to add.
If benchmark tests were added, please run the benchmarks in GitHub Actions
for the consistent environment, and the instructions could accord to:
https://spark.apache.org/developer-tools.html#github-workflow-benchmarks.
-->
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: [email protected]
For queries about this service, please contact Infrastructure at:
[email protected]
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]